OUFTI-1 is a nano-satellite currently being constructed by the students of the University of Liège, Belgium. Its main payload is the D-STAR amateur-radio telecommunication protocol. In this paper, we ... [more ▼]

OUFTI-1 is a nano-satellite currently being constructed by the students of the University of Liège, Belgium. Its main payload is the D-STAR amateur-radio telecommunication protocol. In this paper, we explain how hams will be able to operate OUFTI-1 for D-STAR space communications. The large footprint of OUFTI-1 results in a larger number of users being able to communicate via D-STAR. [less ▲]

We present the design, development, and test of three novel, distinct automatic target recognition (ATR) systems for the recognition of airplanes and, more specifically, non- cooperative airplanes, i.e. airplanes that do not provide information when interrogated, in the framework of passive bistatic radar systems. Passive bistatic radar systems use one or more illuminators of opportunity (already present in the field), with frequencies up to 1 GHz for the transmitter part of the systems considered here, and one or more receivers, deployed by the persons managing the system, and not co-located with the transmitters. The sole source of information are the signal scattered on the airplane and the direct-path signal that are collected by the receiver, some basic knowledge about the transmitter, and the geometrical bistatic radar configuration. The three distinct ATR systems that we built respectively use the radar images, the bistatic complex radar cross-section (BS-RCS), and the bistatic radar cross-section (BS- RCS) of the targets. We use data acquired either on scale models of airplanes placed in an anechoic, electromagnetic chamber or on real-size airplanes using a bistatic testbed consisting of a VOR transmitter and a software-defined radio (SDR) receiver, located near Orly airport, France. We describe the radar phenomenology pertinent for the problem at hand, as well as the mathematical underpinnings of the derivation of the bistatic RCS values and of the construction of the radar images. For the classification of the observed targets into pre-defined classes, we use either extremely randomized trees or subspace methods. A key feature of our approach is that we break the recognition problem into a set of sub-problems by decomposing the parameter space, which consists of the frequency, the polarization, the aspect angle, and the bistatic angle, into regions. We build one recognizer for each region. We first validate the extra-trees method on the radar images of the MSTAR dataset, featuring ground vehicles. We then test the method on the images of the airplanes constructed from data acquired in the anechoic chamber, achieving a probability of correct recognition up to 0.99. We test the subspace methods on the BS-CRCS and on the BS-RCS of the airplanes extracted from the data acquired in the anechoic chamber, achieving a probability of correct recognition up to 0.98, with variations according to the frequency band, the polarization, the sector of aspect angle, the sector of bistatic angle, and the number of (Tx,Rx) pairs used. The ATR system deployed in the field gives a probability of correct recognition of 0.82, with variations according to the sector of aspect angle and the sector of bistatic angle. [less ▲]

We consider the automatic classification of aircraft observed with a passive radar, thus using illuminators of opportunity. We deployed a testbed and developed classification algorithms. Preliminary tests ... [more ▼]

We consider the automatic classification of aircraft observed with a passive radar, thus using illuminators of opportunity. We deployed a testbed and developed classification algorithms. Preliminary tests show a correct recognition rate of 72%. [less ▲]

A major issue in the design of a D-STAR radiocommunication system for a satellite is the issue of Doppler shift compensation. We describe the various constraints we faced, and the solutions we implemented ... [more ▼]

A major issue in the design of a D-STAR radiocommunication system for a satellite is the issue of Doppler shift compensation. We describe the various constraints we faced, and the solutions we implemented on-board and on the ground for the OUFTI-1 nanosatellite system. [less ▲]

We describe the current status of the OUFTI-1 nanosatellite project, the main payload of which is an innovative D- STAR radiocommunication system. We describe the architectures of the ground and space ... [more ▼]

We describe the current status of the OUFTI-1 nanosatellite project, the main payload of which is an innovative D- STAR radiocommunication system. We describe the architectures of the ground and space segments. [less ▲]

We give a very compact account of the overall energy budget of the OUFTI-1 nanosatellite, thereby providing a useful guide for future designs, as well as an explanation of why a nanosatellite can ... [more ▼]

We give a very compact account of the overall energy budget of the OUFTI-1 nanosatellite, thereby providing a useful guide for future designs, as well as an explanation of why a nanosatellite can, energetically, survive and do useful tasks in space. [less ▲]

We describe the principles and performances the OUFTI-1 nanosatellite electrical power supply (EPS), which is designed to provide subsystems with the required voltages and currents, with as high a ... [more ▼]

We describe the principles and performances the OUFTI-1 nanosatellite electrical power supply (EPS), which is designed to provide subsystems with the required voltages and currents, with as high a reliability as possible. [less ▲]

In this paper, we describe a new automatic target recognition method for classifying targets according to their bistatic backscattering coefﬁcients. The classiﬁcation model is based on the construction of ... [more ▼]

In this paper, we describe a new automatic target recognition method for classifying targets according to their bistatic backscattering coefﬁcients. The classiﬁcation model is based on the construction of subspaces, one per target class. Results show an overall correct classiﬁcation rate of about 83%, indicating that our method seems to be valid. Further improvements of the algorithm are also discussed. [less ▲]

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT im- age classiﬁer. It uses randomized sub-windows extraction and extremely randomized ... [more ▼]

In this paper, we describe a new automatic target recognition algorithm for classifying SAR images based on the PiXiT im- age classiﬁer. It uses randomized sub-windows extraction and extremely randomized trees (extra-trees). This approach re- quires very little pre-processing of the images, thereby lim- iting the computational load. It was successfully tested on an extended version of the public standard MSTAR database, that includes targets of interest, false targets, and background clutter. A misclassiﬁcation rate of about three percent has been achieved. [less ▲]